Historically there has been a great deal of effort placed on the accuracy of financial forecasting. For example, when forecasting demand, if you can predict that sales will be a certain amount at a certain time, with a +/- tolerance level, then the supply chain can be optimized to minimize the volume and length of time in which inventory is held before being sold and eventually collected. This decreases working capital needs and increases profits.

Up until the COVID pandemic hit, risk mitigation was not a focus of many companies; the focus was all about capturing upside opportunity. Coincidentally, risk mitigation and opportunity capture are two sides of the same coin. In the example above, a sales forecast that is too accurate may also lead to a forgone conclusion. For example, what if demand is higher than the forecast, but the supply chain is unable to meet the unexpected demand? This robs a company of additional sales, but the sales forecast may still come within the predicted forecast tolerance.

You only need to look at the recent COVID pandemic and the run on toilet paper, paper towels, cleaning products, flour and other high-demand consumables. Making a model too accurate is a common problem and is called overfitting. Scenario planning helps to prevent this by thinking about multiple changes in assumptions, inputs, external forces, actions of competitors, and other variables to produce variations of the future.

More Is Not Always Better

There is usually a desire to add more data points to a forecast scenario in the hopes of improving its accuracy/relevancy, but more data does not actually translate to better or more accurate scenario iteration.

Think of it in economic terms. The value of one additional piece of data, even assuming the perfect predication of that data point, is both priceless and useless at the same time. It’s the actions that one takes around that data point that matter, and all execution is flawed to one degree or another.

There is a base set of data, such as key financial data and drivers, that must be included in all scenarios; but at a certain point the law of diminishing returns comes into play and the time, trouble, and value of adding a new series or variable becomes less effective. This point varies by company, model, and time period, so the financial forecaster must be diligent in pushing back when new data types are inserted into a financial forecast. A thorough review as to relevance and impact to the model must be determined, otherwise you will quickly have a kitchen sink model that is difficult to manage and not effective for decision making. It may not even be accurate compared to a more straight forward model.

When More Is Better

Instead of more data, financial forecasters should focus on increasing the velocity and volume of the scenarios they can create and the development of actionable playbooks which the business can execute as triggers are identified. Although the number of forecast scenarios that one can create is virtually limitless, most companies congregate around having—at a minimum—a low, most likely, and high case.

A financial forecast virtually never follows a straight line. In fact, when a forecast appears as such, it is most likely ineffective. By iterating scenarios through the oscillation of key input variables, a cone of reasonably probable outcomes can be determined over the forecast horizon. Taken even farther, the use of Monte-Carlo simulations can provide probabilities of different outcomes occurring.

Building actionable playbooks based on future uncertainty will then become the norm. The need for reasonable optionality to both capture upside and mitigate downside can even be quantified. For example, the X % increase in safety stock will cost Y. The cost of holding the extra inventory is the cost of the real option, taking into account delays, unexpected increase in demand, supplier cuts or other more global factors.

Don’t Go It Alone

Financial professionals should understand that financial forecasting and scenario development are more akin to art than science. Great financial forecasting and scenario planning must concede to the fact that the future is uncertain—but this uncertainty is exactly why planning is so valuable. Through the forecasting and planning process, business can impart their actions and alter the future much to their benefit.

Optimizing your forecasting and planning process is no easy task and often financial personnel can’t take this on in addition to their regular duties. Using an external partner in conjunction with an internal designate produces the optimal mix of internal knowledge and external resources to produce tangible results.

If your organization is seeking to improve their FP&A process to increase its financial insight, contact MorganFranklin today to take the first step in your journey.

By Ken Fick

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